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Hybrid Column/Row-Oriented DBMS

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Man–Machine Interactions 4

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 391))

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Abstract

The rapid growth of data volumes which store the increasing amount of information makes the necessity of searching for the effective methods of data storing and processing. Some researches on this field recommend changing the row data organization that is classical for DBMS to the columnar one and/or the in-memory approach usage. The article presents chosen hybrid solutions which simultaneously enable storing data both in a row-based way and column-based one, as well as process these data in the in-memory technology.

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Notes

  1. 1.

    Queries included operators: ROLLUP, CUBE, GROUPING SETS, aggregate functions: COUNT, AVG, SUM, ranking functions: RANK, DENSE_RANK and PARTITION BY clause.

  2. 2.

    For a better visualization the differences in speed of query execution in Actian Vectorwise, Infobright, Sybase IQ and MS SQL Server 2012 database systems, the percentage scale on Y axis was used.

  3. 3.

    The INMEMORY_SIZE initialization parameter specifies the amount of memory reserved for use by the IM column store. The larger the in-memory area, the greater the number of database objects that can utilize it.

  4. 4.

    CRITICAL \(>\) HIGH \(>\) MEDIUM \(>\) LOW.

  5. 5.

    The data stored in the in-memory column format is automatically compressed with a set of compression techniques that improve the memory capacity, the query performance or both elements.

  6. 6.

    All row groups were compressed.

  7. 7.

    INMEMORY MEMCOMPRESS FOR QUERY (MFQ), MEMCOMPRESS FOR CAPACITY (MFC), MEMCOMPRESS FOR DML (MFDML) and MEMCOMPRESS FOR QUERY HIGH (MFQH).

References

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Authors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Małgorzata Bach & Aleksandra Werner

Authors
  1. Małgorzata Bach
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  2. Aleksandra Werner
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Corresponding author

Correspondence to Małgorzata Bach .

Editor information

Editors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Aleksandra Gruca

  2. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Agnieszka Brachman

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

  4. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Tadeusz Czachórski

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Bach, M., Werner, A. (2016). Hybrid Column/Row-Oriented DBMS. In: Gruca, A., Brachman, A., Kozielski, S., Czachórski, T. (eds) Man–Machine Interactions 4. Advances in Intelligent Systems and Computing, vol 391. Springer, Cham. https://doi.org/10.1007/978-3-319-23437-3_60

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  • DOI: https://doi.org/10.1007/978-3-319-23437-3_60

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23436-6

  • Online ISBN: 978-3-319-23437-3

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